Why Big Banks Are Betting on AI: It's Not About Innovation—It's About Survival

As Bank of America earmarks $4B for technology this year and JP Morgan's R&D budget hits $17B, digital transformation, and AI transformation in particular, is poised to fundamentally change how asset management works. While these large banks have the balance sheets to weather such investments, many small to mid-sized asset managers do not. Yet as this McKinsey research shows, technology spending surged by 8.9% CAGR over the past five years in North America and Europe, far outpacing spending in other functions.

However, despite this massive investment:

• Cost as a share of AUM (a key productivity metric) has remained relatively flat at the industry level

• Operational expenses in other functions have not contracted despite expectations that technology would create efficiencies

So why are top asset managers and banks making such large investments?

Traditionally, 60%-80% of technology budgets go to "run-the-business" initiatives (maintaining legacy systems), and of the remaining budget, only 5-10% of total tech spend goes toward digital transformation. The realization is dawning that just running in maintenance mode isn't enough. The proof is in the margins.

The Margin Crisis That Changed Everything

Here's what most people miss: pre-tax operating margins declined by 3 percentage points in North America and 5 percentage points in Europe between 2019 and 2023. In North America alone, costs increased 18% over five years while revenues grew only 15% in the same period. That's not sustainable math.

The decade of easy money—low interest rates, stable GDP growth, geopolitical calm—is over. Since 2022, the industry experienced a sharp 10% decline in AUM, and while markets rebounded in 2023, the underlying cost structure remained bloated and revenues became increasingly unpredictable.

Asset managers are trapped. They can't simply cut their way to profitability because they're already spending 60-80% of their tech budgets on keeping the lights on. Legacy systems are eating them alive with what McKinsey calls a "complexity tax": the time and money spent maintaining fragmented, outdated technology stacks.

AI: The Only Way Out

This is why AI isn't just another tech trend for these firms—it's an existential necessity. McKinsey's research shows AI could impact 25-40% of an asset manager's total cost base. For a mid-sized firm with $500 billion AUM, that's transformational.

The early results are promising:

• Client-facing roles: 9% efficiency improvement

• Investment management: 8% efficiency gain

• Risk and compliance: 5% efficiency boost

• Technology functions: 20% efficiency improvement

But here's the catch: just throwing money at AI won't work. The firms that succeed are the ones doing complete domain-level transformation, reimagining entire workflows, not just adding AI tools on top of broken processes.

The Strategic Imperative

One top 30 asset manager McKinsey studied initially tried tackling hundreds of individual AI use cases and failed to see returns. They pivoted to a domain-based strategy, focusing on end-to-end transformation of four functions: operations, marketing, distribution, and investment management. Each effort now has its own P&L and ROI targets.

Another leading firm shifted from teaching employees to code (now irrelevant with AI) to building AI literacy across the organization. They estimate 100,000 hours in annual savings just from query management and workflow automation.

The message is clear: AI transformation isn't about innovation for innovation's sake. It's about survival in an industry where traditional cost management has hit a wall and margins are under relentless pressure.

The firms making these massive investments understand something fundamental: in this new volatile, competitive landscape, AI-driven transformation isn't optional. It's the only viable path back to sustainable profitability.

Those who get it right will pull ahead. Those who don't risk becoming irrelevant.

~Michael J. Prichard, Founder & CEO

TLDR: What you need to know about AI in Finance

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